The Efficacy of Arabic Version of the Developmental Assessment of Young Children Second Edition (DAYC-2) Scale in Detecting Developmental Delay among Jordanian Children Aged Birth to 71 Months
Bibliographic record
Abstract
This study aimed to assess the efficacy of the developmental assessment of young children second edition (DAYC-2) Scale in detecting Developmental Delay among Jordanian children aged birth to 71 months. Firstly, the scale was translated and reviewed for language and cultural appropriateness. Secondly, the Arabic Jordanian version of the scale was administrated to children diagnosed as developmental delay aged from birth to 48 months in the neurodevelopmental pediatric clinic in Jordan university hospital, and on children aged 48 to 71 months who were diagnosed as developmental delay in special education centers in Capital Amman. The scale was administrated also to normal development children aged 0 to71months who visited the Institute for family health–Noor al Hussein foundation and attended preschools in Capital Amman. Total of 310 children aged (0-71months) were enrolled. Construct validity and discriminative validity were verified. Reliability was established through computing Kuder–Richardson Formula 20 (KR-20), test-retest, split half test methods.t-test showed that the scale discriminates between normally developed and developmentally delayed children. One-way ANOVA showed that age has significant effect on the performance of children favoring older age groups using Scheffé multiple comparisons test.Item efficacy was determined by calculating point-biserial correlation coefficients for all items in each domain. The results showed that the scale had good psychometric properties and was capable of detecting developmental delay in children aged from birth to 71 months in Jordan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".